Detecting and Mitigating Fraud at Scale

The presentation below by Eric Levine, Engineering Manager at Airbnb shows how Airbnb’s Trust and Safety team has built machine learning infrastructure from the ground up to catch and defuse fraudsters on the platform. This talk briefly goes through the history of the machine learning platform from its very basic roots to the advanced system that is in place today. The team found that by taking a tightly coupled, naïve implementation to a well-factored, cleanly separated systems, it could individually tune each component to decrease the cycle between bad behavior to well-performing model to catch said behavior, and how it could leverage that introspection to enable real-time detection of issues at scale. Further, by empowering data science to explore new features independently from engineering efforts, the team was able to reduce the time from feature conception to production implementation.

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Industry Perspectives

In this special guest feature, Brian D’alessandro, Director of Data Science at SparkBeyond, discusses how AI is a learning curve, and exploring opportunities within the technology further extends its potential to enable transformation and generate impact. It can shape workflows to drive efficiency and growth opportunities, while automating other workflows and create new business models. While AI empowers us with the ability to predict the future — we have the opportunity to change it. [READ MORE…]

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White Papers

Organizations worldwide are facing the challenge of effectively analyzing their exponentially growing data stores. Download the new white paper from SQream DB that explores the features that make GPU databases ideal for BI and incorporates real-world use-cases from actual customer implementations. It also explains how you can turn your existing BI pipeline into a more capable, next-generation big data analytics system using powerful GPU technology.